How-To Automatically Research Anyone (Advanced)

How-To Automatically Research Anyone (Advanced)

🎙 The AI Advantage 👥 480K 📅 November 28, 2024 ⏱ 181 min 👁 6K 📄 tutorial 🧭 2026-09-08
Available in: English (current) Français

Keywords

automationMake.comLinkedInChatGPTPerplexity

Summary

This live stream from The AI Advantage, hosted by Igor, is an advanced tutorial on building a no-code automation to research individuals using LinkedIn profiles. The automation leverages Make.com to orchestrate Perplexity API for web searches and ChatGPT for data synthesis, ultimately generating a structured report stored in a Notion database. The session begins with a recap of the basic automation and then focuses on extending it with custom data fields, such as a CV or personal notes, to enrich the generated reports. Igor demonstrates the step-by-step process of importing a blueprint, connecting APIs, and configuring the Notion database. He also addresses common issues, such as the ’no access’ error from Perplexity, and shows how to implement retry logic. The stream includes a live demonstration, a Q&A segment, and a guest appearance by Michal, who discusses community automations. Igor also introduces a free AI resource recommendation quiz and shares insights into practical AI applications, including task management for ADHD and the journey of his YouTube channel. The session concludes with a discussion on the value of AI knowledge and time savings, and a preview of upcoming streams.

187 words

Critical Evaluation

Value of the Information & Strength of the Argument

The video provides high practical value by offering a fully functional automation blueprint that viewers can replicate. The argumentation is based on live demonstration and troubleshooting, which adds credibility. The presenter clearly explains the logic behind each step, and the inclusion of error handling and custom data fields addresses real-world needs. The value is further enhanced by the community interaction and the sharing of additional resources like the quiz and templates.

Scientific Rigor, Source Quality, Title Accuracy

The scientific rigor is moderate; the content is a practical tutorial rather than a formal study. The sources cited are primarily the tools used (Make.com, Perplexity, ChatGPT) and the provided templates. The presenter is transparent about limitations, such as the occasional ’no access’ error, which adds honesty. The title accurately reflects the content, as it is an advanced guide to automating research. The description includes links to the blueprint and templates, which are directly relevant. The comments are not provided, so no analysis of public reception is possible.

174 words

Title / Content Match

The title accurately reflects the advanced nature of the tutorial, focusing on extending a previously shown automation with custom data and advanced features.

Quality & Reliability

7/10

The content is a practical tutorial demonstrating a functional automation, with live troubleshooting and transparent discussion of limitations. The methodology is reproducible and the presenter shows real-world application, but the scientific rigor is limited as it is a demonstration rather than a peer-reviewed study.

Chapters

Cited Sources

Concurring Sources

  • Make.com — The platform used for the automation, which is well-documented and widely used.
  • Perplexity AI — The AI search engine used, known for its accuracy and real-time data.

Contribution & Novelties

The video’s original contribution is the extension of a basic automation to include custom data fields, allowing users to incorporate private information (e.g., CVs, transcripts) into AI-generated reports. This adds a layer of personalization and depth to the research process. The live troubleshooting and community interaction also provide practical insights not found in edited tutorials.

Pour aller plus loin :

  • Make.com — The no-code automation platform used in the tutorial.
  • Perplexity AI — The AI search engine used for web research.
  • ChatGPT — The language model used for report generation.
  • Notion — The database and documentation tool used for storing reports.
  • LinkedIn — The professional network used as the primary data source.
  • No-code — Concept of building applications without traditional programming.

121 words

Radar Profile

The radar profile shows a balanced performance across all dimensions, with slightly higher scores in information quantity and technical level, reflecting the tutorial's practical depth. The lower score in information quality and reliability is due to the lack of formal scientific rigor and the reliance on anecdotal evidence.

Reliability 7/10